The field of the disclosure relates generally to signal processing, and, more particularly, to estimating signal parameters based on power spectral density shape.
Wireless communication systems that compete for spectrum usage (such as those operating in white spaces or cognitive radio systems) must determine the presence of existing signals in order to avoid interfering with those existing signals. This determination may be difficult, and involves issues such as the near-far problem. Specifically, while a first signal from an existing transmitter may be far away or weak relative to an additional signal source, a receiver may be much closer to the additional signal source. If the additional signal source sends out a powerful signal in a frequency near a frequency of the first signal, the powerful signal may significantly interfere with the receiver's ability to detect the first signal. This problem is exacerbated further when the first signal is so weak that it is undetectable as an existing signal and simply looks like noise, which could lead to transmission directly on top of the first signal.
With exponential growth in wireless communications, both for civilian and military usage, comes the need to cost effectively and quickly modify a radio device to meet new uses and operate on existing frequencies. The ideal device would be a single physical radio that implements all existing communication signals and protocols, as well as one that adapts to new and future conditions to effectively use different communications resources when desired. Software-defined radio (SDR) technology brings these benefits of flexibility and cost efficiency to end users. In order for SDR to participate with other systems (both SDR and legacy), it must compete for spectrum and cooperate with other systems. In order to cooperate, SDR must be able to sense when other signals are present and avoid interfering with them.
The near-far problem, discussed briefly above, is a problem that exists with current wireless radio networks, including those using direct-sequence spread-spectrum multiple access (DS/SSMA) communication systems, and also systems that must simply determine which legacy (i.e., non-spread) signals are present before deciding on a transmit channel and signal type. For example, code division multiple access (CDMA) type systems achieve multiple-access capability by assigning a distinct signature waveform to each user from a set of waveforms with low mutual cross correlations. Two conditions must be satisfied for this to occur. First, the multi-user CDMA signal set must have low cross-correlations for all possible delays between different user data streams. Second, the power of the received signals must be similar. If either of these conditions is not fulfilled, then bit-error-rate and anti-jamming capabilities of CDMA receivers for multiple users may be degraded. Known solutions include using power control or designing CDMA signals with sharper cross correlation properties.
These issues with CDMA signal sets are also present, albeit modified, in situations where legacy (i.e., non-spread) signals are present. For example, suppose a system includes an SDR or cognitive transceiver that must sense which signals are present and must decide, among other things, i) what legacy receiver systems should be supported, ii) what signal types to transmit (CDMA, frequency-shift keying, binary phase-shift keying, quadrature phase-shift keying, etc.), iii) what signals parameters to use (frequency, duration, time slots, etc.), iv) what data rates to support, v) what power levels to use, and/or vi) what data latency to support. These decisions will be partially based on the types and powers of signals already present. Specifically, in order to coexist in a competitive spectrum environment, signals to be transmitted must not substantially interfere with current signals, and must not be substantially interfered with by current signals.
At least some known methods to solve this non-interference problem have limited ability to operate at relatively low signal to noise ratios (SNRs), leading to incorrect decisions about the presence of legacy signals and therefore incorrect decisions about the signals to transmit. To overcome this, in certain circumstances, correlation can be performed using specific knowledge about existing signal preambles to operate at low SNR levels. However, such methods require substantial foreknowledge, which is not likely to be available, and only applies to digital signals.